Designing Cybersecurity Measures for Enterprise Software Applications to Protect Data Integrity

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(8), С. 1920 - 1941

Опубликована: Авг. 23, 2024

In an era of escalating cyber threats, safeguarding data integrity in enterprise software applications is critical for maintaining trust and operational stability. Designing robust cybersecurity measures essential to protect sensitive information from unauthorized access, alteration, loss. This review explores key strategies methodologies developing comprehensive frameworks tailored applications. Effective begins with a thorough risk assessment identify potential vulnerabilities threats specific the enterprise's environment. Implementing multilayered security measures, including encryption, access controls, authentication protocols, vital mitigating risks. Encryption protects transit at rest, ensuring that even if intercepted, remains unintelligible parties. Access controls mechanisms, such as multifactor (MFA), enhance by verifying identity users restricting based on roles permissions. Regular audits vulnerability assessments play crucial role detecting addressing weaknesses. These should be conducted both internally externally provide view posture. Additionally, adopting secure coding practices integrating into development lifecycle (SDLC) help identifying during phase. Incident response planning another aspect cybersecurity. Developing well-defined incident plan ensures can quickly effectively address breaches, minimizing damage restoring integrity. includes establishing protocols detecting, responding to, recovering incidents. Educating training employees about best Employees aware common phishing social engineering attacks, understand their enterprise’s data. conclusion, designing effective requires multifaceted approach assessment, regular audits, practices, planning, employee training. By implementing these strategies, enterprises defenses, integrity, ensure resilience against evolving threats. Keywords: Designing, Cybersecurity, Data Integrity, Software Applications, Enterprise.

Язык: Английский

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Enhancing software development practices with AI insights in high-tech companies

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(8), С. 1897 - 1919

Опубликована: Авг. 23, 2024

Artificial Intelligence (AI) is revolutionizing software development practices in high-tech companies, providing transformative insights and tools that enhance productivity, quality, efficiency. This review explores the integration of AI into processes, highlighting its impact on key areas such as code generation, bug detection, project management, testing. AI-driven are enabling developers to automate repetitive tasks, optimize code, identify potential issues before they become critical, thus reducing time improving reliability. Machine learning algorithms analyze vast amounts data from past projects provide predictive analytics, guiding teams decision-making resource allocation. Natural language processing (NLP) facilitates more intuitive interactions with tools, streamlining communication collaboration among team members. Furthermore, enhances continuous deployment (CI/CD) pipelines by automating testing stages, ensuring changes seamlessly integrated deployed minimal human intervention. By leveraging AI, companies can adopt agile methodologies, respond swiftly market changes, deliver high-quality products. The also discusses challenges integrating development, including need for substantial initial investment, complexity models, importance privacy security. Solutions fostering a culture learning, investing AI-specific training developers, establishing robust governance frameworks essential overcoming these barriers. In conclusion, offer significant advantages them their practices, achieve greater efficiency, maintain competitive edge rapidly evolving technological landscape. Embracing advancements requires strategic approach, investment technologies training, fully harness drive innovation development. Keywords: Software Development, High-Tech, Practices, Companies.

Язык: Английский

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Predictive Analytics

Advances in marketing, customer relationship management, and e-services book series, Год журнала: 2025, Номер unknown, С. 463 - 492

Опубликована: Янв. 17, 2025

Predictive analytics, leveraging machine learning and big data, has emerged as a transformative tool in business consumer behavior forecasting. This study explores the application of predictive models to anticipate market trends, optimize decision-making, enhance customer engagement. Integrating algorithms with data enables businesses analyze vast amounts structured unstructured uncovering patterns that drive actionable insights. Results highlight synergistic relationships among capabilities, such real-time availability source utilization, while emphasizing foundational role robust technical infrastructure. Managerial implications underscore need for balanced development capabilities strategic integration systems into decision-making processes. contributes understanding how organizations can effectively deploy analytics achieve competitive advantage.

Язык: Английский

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Implementing AI Accuracy, Learning Rate, Inference Time on enhancing Big Data Analysis and Strategic Plan

Data & Metadata, Год журнала: 2025, Номер 4, С. 637 - 637

Опубликована: Янв. 22, 2025

Introduction: This study aims to focus on the role of artificial intelligence tools and capabilities such as accuracy, learning rate inference time in influencing big data analysis building strategic plans at Zain Jordan Telecommunications Company. Objective: The review explores how increasing ability organizations maintain competitive an era continuous change development field information technology, most adopting new tactics features improve organizational performance, services provided customers, simplify administrative operational processes, efficiency make decisions. Method: A research questionnaire was distributed impact measure plans. 163 valid questionnaires were received for analyzed using PLSSIM system.Result: Artificial rates positively affect plans.Conclusion: this allows a deeper understanding

Язык: Английский

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Riding into the Future: Transforming Jordan’s Public Transportation with Predictive Analytics and Real-Time Data

Data & Metadata, Год журнала: 2025, Номер 4, С. 887 - 887

Опубликована: Апрель 4, 2025

Introduction: This study explores how predictive analytics and real-time data integration can improve efficiency in Jordan’s public transportation network. By addressing scheduling, route optimization, congestion management, it responds to growing urban transit demands the region.Methods: Data were collected over three months from official ridership logs, GPS-enabled buses, traffic APIs. ARIMA-based time-series forecasting captured historical trends, while a Random Forest model incorporated index, average wait times, other operational variables. Metadata management protocols (JSON/XML) facilitated cross-agency sharing.Results: ARIMA proved effective for short-term passenger demand projections, although occasionally underpredicted sudden peaks. The approach yielded stronger overall accuracy, explaining roughly 85% of variation when combining with records. Real-time streams further supported dynamic scheduling adjustments.Conclusion: Combining models IoT-based enhance reliability user satisfaction system. Although limited by timeframe scope, findings underscore importance multi-agency collaboration ongoing policy support sustain data-driven innovations.

Язык: Английский

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Methodologies for developing scalable software frameworks that support growing business needs

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(8), С. 2661 - 2683

Опубликована: Авг. 21, 2024

Developing scalable software frameworks is critical for businesses looking to support growth and adapt changing demands. This review explores methodologies creating robust, architectures that can handle increasing workloads evolving business requirements. It highlights key principles, such as modularity, flexibility, performance optimization, which are essential design. Central this discussion the use of microservices architecture, breaks down applications into smaller, independent services be developed, deployed, scaled independently. approach enables respond quickly market changes scale specific parts their systems without affecting entire application. Additionally, cloud computing plays a pivotal role in scalability, providing necessary infrastructure dynamically allocate resources based on demand. Leveraging cloudnative technologies like containers orchestration tools Kubernetes ensures efficiently managed diverse environments. Another methodology adoption DevOps practices, foster culture collaboration between development operations teams. Continuous integration continuous deployment (CI/CD) pipelines automate delivery process, allowing faster releases more reliable updates. reduces downtime new features improvements implemented meet needs. Data management strategies also contribute scalability. Implementing distributed databases using NoSQL large volumes data provide high availability fault tolerance. Effective caching mechanisms load balancing further enhances system responsiveness. Monitoring analytics maintaining Tools realtime insights user behavior enable proactive optimization. allows identify potential bottlenecks preemptively. In conclusion, developing requires combination architectural modern technologies, best practices. By embracing microservices, computing, DevOps, effective management, robust monitoring, create solutions future challenges. Investing these remain resilient, responsive, capable meeting needs business. Keywords: Support, Business Needs, Methodologies, Scalable Software, Framework.

Язык: Английский

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Assessing the transformative impact of cloud computing on software deployment and management

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(8), С. 2062 - 2082

Опубликована: Авг. 31, 2024

Cloud computing has fundamentally transformed the landscape of software deployment and management, offering significant benefits reshaping traditional approaches. This review explores transformative impact cloud on these domains, highlighting key changes advantages. Firstly, revolutionized by introducing scalable flexible infrastructure solutions. Unlike onpremises systems that require upfront investment ongoing maintenance, platforms offer ondemand resources payasyougo models. shift enables organizations to deploy rapidly, adapt changing needs, scale efficiently without constraints physical hardware. Additionally, enhances management through centralized control automation. environments provide integrated tools streamline deployment, monitoring, maintenance applications. These facilitate automated updates, patch system backups, reducing burden IT teams minimizing downtime. Furthermore, cloudbased realtime visibility analytics, allowing for proactive performance monitoring troubleshooting. The collaborative nature also fosters improved development practices. support DevOps methodologies enabling continuous integration delivery (CI/CD) pipelines. accelerates cycles, collaboration among distributed teams, ensures consistent reliable deployments. Moreover, cloud's global reach accessibility break down geographical barriers, across multiple regions effortlessly. geographic flexibility user experience high availability performance, regardless user's location. Despite advancements, transition presents challenges, including data security compliance concerns. Organizations must implement robust measures adhere regulatory requirements protect sensitive information maintain trust. In conclusion, had a profound scalable, flexible, efficient Its effects include streamlined operations, collaboration, accessibility. As technology continues evolve, navigate associated challenges while leveraging its drive innovation efficiency in management. Keywords: Management, Impact, Computing, Software Deployment, Assessing

Язык: Английский

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Decision‐Making in M&A Under Market Mispricing: The Role of Deep Learning Models

Managerial and Decision Economics, Год журнала: 2025, Номер unknown

Опубликована: Апрель 4, 2025

ABSTRACT In the ever‐evolving landscape of financial markets, mergers and acquisitions (M&A) play a pivotal role in shaping corporate ecosystem. However, presence market mispricing, driven by various factors such as information asymmetry, behavioral biases, external shocks, has been persistent challenge for investors corporations alike. Understanding intricate relationship between stock mispricing M&A is crucial making informed investment decisions fostering resilient environment. This research explores how impacts within fragmented setting, utilizing deep learning methods to uncover complex patterns relationships. By analyzing inefficiencies, study aims provide deeper understanding influences strategies outcomes. Employing quantitative descriptive design, gathered valid data through distributed questionnaires, yielding responses from 130 traders, 115 participants, 99 regulators policymakers. The analysis was conducted using Statistical Package Social Sciences (SPSS). Firstly, it establishes effectiveness algorithms detecting quantifying providing reliable measure its extent. then differential performance outcomes companies engaging during periods prevalent compared those efficient pricing. study's novel contribution lies introduction sentiment models incorporate participants' sentiments, enhancing accuracy detection impact on activity. Finally, this contributes valuable insights into integration techniques leveraging strategic decision‐making context M&A.

Язык: Английский

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Leveraging big data to inform strategic decision making in software development

International Journal of Applied Research in Social Sciences, Год журнала: 2024, Номер 6(8), С. 1848 - 1867

Опубликована: Авг. 21, 2024

The rapid advancement of technology has led to an explosion big data, which presents a wealth opportunities for informing strategic decision-making in software development. This review explores how leveraging data can transform the development process by enhancing at various stages. Big analytics provides insights into user behavior, preferences, and trends, enabling developers create more user-centric products. By analyzing large datasets, identify patterns predict future needs, ensuring that solutions are not only relevant but also innovative. In planning phase, helps understanding market demands competition, allowing better resource allocation project prioritization. During development, real-time guide optimization code, enhance performance testing, improve quality assurance processes. Post-deployment, facilitates continuous improvement through detailed analysis feedback usage patterns, leading timely updates feature enhancements. Furthermore, plays crucial role risk management identifying potential issues before they escalate, thus mitigating failures. Predictive analytics, powered forecast challenges provide actionable address them proactively. reduces downtime enhances reliability Strategic benefits from integration with artificial intelligence machine learning algorithms. These technologies automate repetitive tasks, intelligent recommendations, personalize experiences, making efficient effective. However, comes challenges, such as privacy security, managing sheer volume maintaining quality. Addressing these requires robust governance frameworks adherence ethical standards. conclusion, processes holds significant promise. It empowers efficient, reliable, solutions, ultimately driving innovation competitive advantage rapidly evolving tech landscape. evolution tools techniques will further their impact on Keywords: Leveraging, Data, Decision making, Software Development, Inform.

Язык: Английский

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Advancing financial inclusion and technological innovation through cutting-edge software engineering

Finance & Accounting Research Journal, Год журнала: 2024, Номер 6(8), С. 1320 - 1348

Опубликована: Авг. 3, 2024

Advancing financial inclusion and fostering technological innovation through cutting-edge software engineering are paramount in addressing the global disparities access to services. This paper explores critical role of revolutionizing sector, particularly enhancing for underserved populations. Financial inclusion, which ensures that individuals businesses have useful affordable products services, is a cornerstone economic development. Despite its importance, significant portion population remains unbanked or underbanked, primarily due limited traditional banking infrastructure. Technological innovation, driven by advancements engineering, presents transformative solution this challenge. Cutting-edge practices at forefront developing robust, scalable, secure solutions. Mobile applications, instance, leverage sophisticated architectures provide seamless services users remote areas. These applications facilitate various transactions, including money transfers, bill payments, savings, thereby integrating into formal system. Additionally, blockchain technology, underpinned advanced offers decentralized platform transactions. Blockchain's inherent transparency security features make it an ideal tool trust reducing fraud By enabling low-cost cross-border technology significantly contributes making accessible those previously excluded. Artificial Intelligence (AI) machine learning, powered algorithms, further enhance providing personalized AI-driven chatbots virtual assistants offer 24/7 customer support, ensuring constant guidance. Moreover, AI algorithms analyze user data tailored products, such as customized loan investment advice, meeting unique needs diverse users. promising potential, integration these technologies faces challenges, privacy navigating regulatory landscapes. However, strategic collaboration between institutions, providers, bodies, challenges can be mitigated. In conclusion, advancing not only bridges gap but also drives more inclusive economically empowered society. Keywords: Inclusion, Innovation, Advancing, Software Engineering, Cutting-Edge.

Язык: Английский

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